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, volumetric analysis, and modeling of structural heterogeneity in biological macromolecules. Rather than only applying established workflows, you will explore new computational formulations and alternative ways
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assembled genome construction, gut microbial genome, and gene database development. Comfortable working in a diverse, inclusive, interdisciplinary, and highly collaborative environment. Ability to navigate
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About the opportunity: Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and
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representations Analysis of structure–function relationships between morphology and movement Modelling genome–phenotype relationships using machine learning and genomic language models The project offers a unique
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, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the
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to work both independently and in collaborative, interdisciplinary environments. Creativity, initiative, and a structured approach to complex data analysis are essential. Motivation and Fit: A well
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pairs. The student will analyse a unique dataset of chromosome-scale genome assemblies and population genomic data to identify structural variants and adaptive mutations associated with genome duplication
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human
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studies. About the DDLS program Data-driven life science (DDLS) combines data, computational methods, and artificial intelligence to study biological systems from molecular structures to human health and